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莫彩利; 王立忠; 赵建博; 王森; 周皓骏; 任茂栋

doi:10.37188/CO.2023-0103

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doi: 10.37188/CO.2023-0103

莫彩利 ^{1, 3,},
王立忠 ^{1, 2,,},
赵建博 ^{2, 3},
王森 ^{1, 3},
周皓骏 ^{2, 3},
任茂栋 ³

1.
新疆大学机械工程学院, 新疆乌鲁木齐 830046
2.
西安交通大学机械工程学院机械制造系统工程国家重点实验室, 陕西西安 710049
3.
新拓三维技术有限公司创新实验室, 广东深圳 518060

基金项目:国家重点研发计划(No. 2022 YFB4601802)

详细信息

作者简介:
莫彩利（1995—），女，河南洛阳人，硕士研究生，2018年于长安大学获得学士学位，主要从事三维光学测量方面的研究。E-mail：[email protected]

王立忠（1968—），男，山东梁山人，博士，教授，博士生导师，2004年于西安交通大学获得博士学位，主要从事三维光学测量技术的研究。E-mail：[email protected]

中图分类号:TP391.7；TH741
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- 网络出版日期: 2023-09-22

365彩票官网彩票

MO Cai-li ^{1, 3
,},
WANG Li-zhong ^{1, 2
,,},
ZHAO Jian-bo ^{2, 3},
WANG Sen ^{1, 3},
ZHOU Hao-jun ^{2, 3},
REN Mao-dong ³

1.
School of Mechanical Engineering, Xinjiang University, Urumqi 830046, China
2.
State Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
3.
Innovation Lab, XTOP 3D Technology Co. Ltd, Shenzhen 518060, China

Funds:Supported by National Key Research and Development Program (No. 2022 YFB4601802)

More Information

Corresponding author: [email protected]

摘要

摘要:
小尺寸零件的表面积小、结构复杂，传统标志点拼接方法需要在零件表面人工粘贴标志点，导致表面的测量数据缺失成为孔洞；基于特征的点云拼接方法要求零件表面具有易区分的几何或距离特征，不适用于包含重复性特征的回转体零件。本文提出一种基于机械拼接的无标志点扫描测量方法，不需要粘贴标志点，不依赖于零件表面特征。首先，采用基于摄影测量的相机标定方法重建标定板上靶点的高精度三维坐标，通过跟踪编码靶点的位置建立转台不同转角对应的旋转矩阵，进而解算出转轴方向向量和轴上定点坐标，实现转轴和相机的同步标定。其次，在完成两个转轴位姿精确标定的基础上，利用转台转角构建旋转拼接矩阵，实现多视角点云粗配准。最后，基于法向迭代最近点算法(Normal Iterative Closest Point, NICP)完成点云的精配准。实验结果表明：使用靶点跟踪法标定后的两转轴夹角误差较传统的标准球拟合法低0.023°，标定后测量标准球的整体平均尺寸误差小于0.012 mm；在小尺寸零件自动化测量时，机械拼接方法在精配准后的点云拼接效果与标志点拼接方法相近，且拼接稳定性更高。机械拼接方法适用于无法粘贴标记点的小尺寸零件三维形貌测量场景。
- 结构光 /
- 机械拼接 /
- 小尺寸零件 /
- 转轴标定 /
- NICP算法
Abstract:
Small size parts have a small surface area and complex structure. The traditional mark splicing method needs to manually paste marks on the surface of parts, resulting in missing the measurement data of the surface and becoming holes. The feature splicing method requires the surface of parts to have easily distinguishable geometric or distance features, which are not suitable for rotating parts containing repetitive features. We propose a scanning measurement method without marks based on mechanical splicing, which does not need to paste marks or depend on the surface features of parts. First, the camera calibration method based on photogrammetry is used to reconstruct the high precision 3D coordinates of the target on the calibration board. By tracking the position of the encoded target, the rotation matrix corresponding to different angles of the turntable is established, and the direction vector of the rotation axis and the fixed point coordinates on the axis are solved. Then the synchronous calibration of the rotation axis and the camera is completed. Second, based on the accurate calibration of poses of two rotation axes, the rotation mosaic matrix is constructed by using the turntable angle to realize the rough registration of multi-view point clouds. Finally, based on the Normal Iterative Closest Point (NICP) algorithm, the fine registration of the point clouds is completed. Experimental results show that the angle error between the two rotation axes calibrated by the target tracking method is 0.023° lower than that of the traditional standard ball fitting method. After calibration, the average size error of the standard ball is less than 0.012 mm. In the automatic measurement of small-size parts, the point cloud splicing effect of the mechanical splicing method after fine registration is similar to that of the mark splicing method, and the splicing stability is higher. The mechanical splicing method is suitable for the 3D topography measurement of small-size parts where the marks cannot be pasted.
- Structured light /
- mechanical splicing /
- small-size parts /
- axis calibration /
- NICP algorithm

HTML全文

图 1 无标志点扫描测量方法的流程图

Figure 1. Flowchart of the scanning measurement method without marks

下载: 全尺寸图片幻灯片

图 2 针孔相机成像模型

Figure 2. Imaging model of pinhole camera

下载: 全尺寸图片幻灯片

图 3 相机标定过程图

Figure 3. Camera calibration process diagram

下载: 全尺寸图片幻灯片

图 4 标定板图像

Figure 4. Image of calibration board

下载: 全尺寸图片幻灯片

图 5 标准球拟合法标定单个转轴位姿

Figure 5. Calibration of single rotation axis pose using standard ball fitting method

下载: 全尺寸图片幻灯片

图 6 多视角点云旋转拼接原理图

Figure 6. Schematic diagram of multi-view point cloud rotation splicing

下载: 全尺寸图片幻灯片

图 7 绕空间任意转轴的旋转变换关系

Figure 7. The rotation transformation relation around any rotation axis in space

下载: 全尺寸图片幻灯片

图 8 NICP算法流程图

Figure 8. Flowchart of NICP algorithm

下载: 全尺寸图片幻灯片

图 9 (a)桌面式数控转台光学测量系统及(b)示意图

Figure 9. (a) Tabletop CNC turntable optical measurement system and (b) its schematic diagram

下载: 全尺寸图片幻灯片

图 10 基于标准球的精度验证实验

Figure 10. Accuracy verification experiment based on standard ball

下载: 全尺寸图片幻灯片

图 11 标准球机械拼接绝对值误差统计结果

Figure 11. Statistical results of absolute value error of standard ball mechanical splicing

下载: 全尺寸图片幻灯片

图 12 小尺寸零件的点云拼接效果图

Figure 12. Point cloud splicing effect diagrams of small-size parts

下载: 全尺寸图片幻灯片

表 1 相机标定内参数

Table 1. Camera calibration internal parameters

内参数	左相机	右相机
f/pixel	4666.2300	4666.5600
$ {x}_{0}/pixel $	47.6090	−14.4401
$ {y}_{0}/pixel $	10.2786	−14.5546
$ {K}_{1} $	−3.4003e−09	−4.1734e−09
$ {K}_{2} $	1.1598e−15	1.8279e−15
$ {K}_{3} $	1.8523e−22	−2.2075e−23
$ {P}_{1} $	−7.4732e−08	1.5797e−08
$ {P}_{2} $	1.0306e−08	−2.0569e−09
$ {b}_{1} $	1.2749e−4	2.4643e−06
$ {b}_{2} $	−2.2662e−05	3.9066e−05

下载: 导出CSV

表 2 相机标定外参数

Table 2. Camera calibration external parameters

相机编号	${{\boldsymbol{R}}_C}$			${{\boldsymbol{T}}_C}$
左相机	1	0	0	0
	0	1	0	0
	0	0	1	0
右相机	0.8992	−0.0098	0.4374	176.2110
	0.0063	0.9999	0.0094	−0.1690
	−0.4374	−0.0057	0.8992	−40.5125

下载: 导出CSV

表 3 标准球拟合法与所提方法的对比

Table 3. Comparison between standard ball fitting method and proposed method

实验编号	标准球拟合法^{[ 22 ]}			文中所提方法
实验编号	夹角/°	点积	夹角误差/°	夹角/°	点积	夹角误差/°
1	89.938	0.001078	0.062	89.962	0.000666	0.038
2	89.923	0.001341	0.077	89.949	0.000883	0.051
3	89.934	0.001145	0.066	89.962	0.000658	0.038
4	89.939	0.001072	0.061	89.955	0.000786	0.045
5	89.940	0.001048	0.060	89.961	0.000686	0.039
6	89.929	0.001245	0.071	89.965	0.000604	0.035
7	89.938	0.001079	0.062	89.952	0.000838	0.048
8	89.938	0.001085	0.062	89.947	0.000922	0.053
9	89.939	0.001058	0.061	89.965	0.000606	0.035
10	89.940	0.001048	0.060	89.967	0.000583	0.033
平均	89.936	0.001120	0.064	89.959	0.000723	0.041

下载: 导出CSV

表 4 不同点云拼接方式的精度对比

Table 4. Accuracy comparison of different point cloud splicing methods unit: mm

实验对象	特征拼接^{[ 13 ]}	标志点拼接^{[ 9 - 10 ]}	机械拼接
实验对象	特征拼接^{[ 13 ]}	标志点拼接^{[ 9 - 10 ]}	粗配准	精配准
注塑件	0.0116	0.0098	0.1135	0.0102
假牙	0.0124	0.0106	0.1213	0.0113
涡轮	0.6845	0.0129	0.1265	0.0123
平均误差	0.2362	0.0111	0.1204	0.0113

下载: 导出CSV

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